dpo-selective-buffer-safeipo – AI Model by wxzhang | AlphaNeural AI

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wxzhang/
dpo-selective-buffer-safeipo

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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dpo-selective-buffer-safeipo

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 4449.9023
Rewards/chosen: -0.8766
Rewards/rejected: -0.9587
Rewards/accuracies: 0.6161
Rewards/margins: 0.0822
Rewards/safe Rewards: -0.8653
Rewards/unsafe Rewards: -0.8608
Logps/rejected: -198.0037
Logps/chosen: -228.0047
Logits/rejected: 1.7482
Logits/chosen: 0.9054

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-07
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Rewards/safe Rewards	Rewards/unsafe Rewards	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
5410.1973	0.27	500	4657.3340	-0.6508	-0.7493	0.6367	0.0984	-0.6382	-0.6354	-177.0600	-205.4323	0.6948	-0.0099
5634.6316	0.53	1000	4507.8945	-0.8000	-0.8748	0.6152	0.0748	-0.7886	-0.7846	-189.6167	-220.3491	1.1542	0.4120
5749.5141	0.8	1500	4458.4429	-0.8858	-0.9723	0.6194	0.0865	-0.8741	-0.8700	-199.3641	-228.9305	1.9547	1.0718

Framework versions

Transformers 4.36.2
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.0